#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import sys
import math
sys.path.extend(["..","../networks","../generators","../simulations"])
from moose_utils import * # imports moose
from OBNetwork import *
from stimuliConstants import * # has SETTLETIME
from simset_inhibition import * # has REALRUNTIME
from sim_utils import * # has setup_tables(), plot_extras() and build_tweaks()
from moose_utils import *
RUNTIME = REALRUNTIME + SETTLETIME
# Whether to inject the current into tuft or soma, typically soma
TUFT_INJECT = False
from pylab import * # part of matplotlib that depends on numpy but not scipy
## Run: python2.6 inhibition.py <PGvsGranule|PGvsGranuleIPSC|lateral_granule>
#-----------------------------------------------------------
class lateral_granule_inhibition:
def __init__(self):
pass
def setup_stim(self,network,args):
if SPIKEBLOCK:
print "Blocking Na in mitral cells only"\
" (don't have granules, else inconsistent) ..."
for cell in network.mitralTable.values():
#blockChannels(cell, ['Na','K2']) # only K2 i.e. Kfast, not all K
blockChannels(cell, ['Na']) # only TTX, only Na blocked not K2
iAinject = offInject
iBinject = onInject
ipulse_duration = 400e-3#150e-3#400e-3 # seconds
## 1-1200pA for 400ms was used by Arevian et al to generate FvsI curves.
## I seem to be using much larger currents - increase the inhibition
if TUFT_INJECT:
tuftsegname = 'Seg0_prim_dend_5_20'
#tuftsegname = 'Seg0_glom_81_102'
print "injecting into tuft/tuft-base segment",tuftsegname
self.compA = moose.Compartment(network.mitralTable[mitralidx].path+'/'+tuftsegname)
self.compB = moose.Compartment(network.mitralTable[mitralsidekickidx].path+'/'+tuftsegname)
self.mitAtuftbaseTable = setupTable('mittuftbaseTable',self.compA,'Vm')
else:
self.compA = network.mitralTable[mitralidx].soma
self.compB = network.mitralTable[mitralsidekickidx].soma
iA = setup_iclamp(self.compA, '_mitralA', SETTLETIME, ipulse_duration, iAinject)
## 1-1200pA for 400ms was used by Arevian et al to generate FvsI curves.
## slightly stagger the start of current pulses in the two cells
## so that the mitrals do not continuously co-fire.
iB = setup_iclamp(self.compB,'_mitralB', SETTLETIME-50e-3, ipulse_duration+50e-3, iBinject)
## To check backpropagating AP, check at various distances from the soma on the lateral dendrites.
dend_seg = moose.Compartment(network.mitralTable[mitralidx].path+\
#'/Seg0_sec_dendp4_0_254') # at 43.86 microns from soma
#'/Seg0_sec_dendd3_0_204') # at 190.56 microns from soma
'/Seg0_sec_dendd4_2_269') # at 1004.47 microns from soma
self.mitAdendTable = setupTable('mitdendTable',dend_seg,'Vm')
dend_seg = moose.Compartment(network.mitralTable[mitralsidekickidx].path+\
#'/Seg0_sec_dendp4_0_254') # at 43.86 microns from soma
#'/Seg0_sec_dendd3_0_204') # at 190.56 microns from soma
'/Seg0_sec_dendd4_2_269') # at 1004.47 microns from soma
self.mitBdendTable = setupTable('mitdendTable',dend_seg,'Vm')
print "Glomerulus segment of mitral A = ", network.mitralTable[mitralidx].glom.path
print "Glomerulus segment of mitral B = ", network.mitralTable[mitralsidekickidx].glom.path
print 'Injecting mitral A with '+str(iAinject)+' and B with '+str(iBinject)
def run_inhibition(self,network,args):
resetSim(network.context, SIMDT, PLOTDT) # from moose_utils.py sets clocks and resets
network.context.step(RUNTIME)
timevec = arange(0.0,RUNTIME+1e-10,SIMDT)*1000
fig = figure(facecolor='w')
ax = fig.add_subplot(111)
#ax.set_title('mitral A',size='large')
#plot(plotBins(network.mitralTable[str(mitralidx)]._vmTableSoma),'r-,')
#plot(plotSpikes(network.mitralTable[str(mitralidx)]._vmTableSoma),'r-,')
plot(timevec,array(network.mitralTable[mitralidx]._vmTableSoma)*1000,\
'r',linestyle='-',linewidth=2.0,label='soma')
if TUFT_INJECT:
plot(timevec,array(self.mitAtuftbaseTable)*1000,\
'b',linestyle='--',linewidth=2.0,label='tuft base')
else:
plot(timevec,array(network.mitralTable[mitralidx]._vmTableGlom)*1000,\
'b',linestyle='--',linewidth=2.0,label='tuft')
plot(timevec,array(self.mitAdendTable)*1000,\
'g',linestyle='-.',linewidth=2.0,label='lat dend')
biglegend()
axes_labels(ax,"time (ms)","Vm (mV)")
figure(facecolor='w')
title('mitral B')
#plot(plotBins(network.mitralTable[str(mitralsidekickidx)]._vmTableSoma),'g-,')
#plot(plotSpikes(network.mitralTable[str(mitralsidekickidx)]._vmTableSoma),'g-,')
plot(timevec,network.mitralTable[mitralsidekickidx]._vmTableSoma,'r-,',label='Soma')
plot(timevec,network.mitralTable[mitralsidekickidx]._vmTableGlom,'b-,',label='Glom')
plot(timevec,self.mitBdendTable,'g-,',label='Dend')
legend()
#----------------------------------------------------------------
class PGvsGranule:
def __init__(self):
pass
def setup_stim(self,network,args):
mitstr = "mitrals_"+str(mitralidx) # mitralidx from simset_inhibition.py
#### Connect a short current injector into a granule_single to generate an AP.
#### This granule_single must connect to our mitral number mitralidx
found_granmitsyn = False
# the post_segment on the mitral must be ~= required_distance from the soma.
self.required_distance = args[0] # meters
dist_list = []
for proj in network.projectionDict.values(): # see NetworkML_reader.py for projectionDict format
# is 'granules_singles' part of the source population name and 'mitral' part of target:
if 'granules_singles' in proj[0] and 'mitrals' in proj[1]:
#### The same granule_mitral_GABA SynChan is used for multiple connections
#### (each SynChan has an array of inputs)
#### I don't want to change the Gbar for a SynChan multiple times, so maintain a unique list.
conn_changed = {}
for conn in proj[2]: # loop through the connections that are part of this projection
if mitstr in conn[2]: # if mitral_<mitralidx> is in the post_segment_path
post_segment = moose.Compartment(conn[2])
### I correct ALL the granule-|mitral Gbar for different clubbing of PGs vs granules
### I only activate the synapses I am interested in so it doesn't matter what I do to others!
granmitsyn = moose.SynChan(get_matching_children(post_segment, ['granule_mitral_GABA'])[0])
if granmitsyn.path in conn_changed: continue
conn_changed[granmitsyn.path] = True
print 'original', granmitsyn.path, granmitsyn.Gbar
mitsoma = network.mitralTable[mitralidx].soma
distance = sqrt( (post_segment.x-mitsoma.x)**2 \
+ (post_segment.y-mitsoma.y)**2 + (post_segment.z-mitsoma.z)**2 )
dist_list.append( (abs(distance-self.required_distance), conn, distance) )
# linear scaling by factor 20 - suspect!!!
granmitsyn.Gbar = granmitsyn.Gbar*PG_CLUB/GRANS_CLUB_SINGLES
dist_list.sort()
distdiff,conn,self.dist = dist_list[0]
print "Lateral compartment is at",self.dist,"meters."
self.dendsegpath = conn[2]
post_seg = moose.Compartment(self.dendsegpath) # wrap post_segment_path conn[2]
#printRecursiveTree(post_seg.id,2)
## take the cellname part [-2] of pre_segment_path conn[1],
## then take the last [-1] id part of cellname
granidx = string.split( string.split(conn[1],'/')[-2], '_' )[-1]
gran = network.populationDict['granules_singles'][1][int(granidx)]
## assumes at least one soma and takes the first!
gran.soma = moose.Compartment(get_matching_children(gran, ['Soma','soma'])[0])
gran_inject = 0.25e-9 # Amperes
ipulse_duration = 5e-3 # seconds
igran = setup_iclamp(gran.soma, '_gran', SETTLETIME+100e-3, ipulse_duration, gran_inject)
self.granTable = setupTable('granTable',gran.soma,'Vm')
self.granDendTable = setupTable('granDendTable',moose.Compartment(conn[1]),'Vm') # pre_segment
### measure the Vm in the post_segment of the mitral
self.mitdendTable = setupTable('mitdendTable',post_seg,'Vm')
break # only one segment needed.
if args[1] == 'IPSC': # voltage clamp mitral soma
#### Since Dong et al use a Ca chelator and TEA (K blocker) in the Vclamp pipette,
#### I block Ca and K channels in the mitral cell
blockChannels(network.mitralTable[mitralidx], ['K','Ca']) # in moose_utils.py
## PID gain: I think for Davison 4-comp-mitral/granule: 0.5e-5 # optimal gain
## too high 0.5e-4 drives it to oscillate at high frequency,
## too low 0.5e-6 makes it have an initial overshoot (due to Na channels?)
## But for BBmit1993, gain of 1e-6 is optimal
self.PIDITable = setup_vclamp(mitsoma, '_somavclamp', 0, RUNTIME+150e-3, 0.0e-3, gain=1e-6)
self.mitITable = setupTable('mitITable',mitsoma,'Im')
#### Find any one PG that connects to our mitral number mitralidx
#### Connect a short current injector into this PG to generate an AP.
#### Find the number of synapses between this PG and this mitral mitralidx
#### and normalize by it to compare with granule.
found_PGmitsyn = False
mitSegsList = []
for proj in network.projectionDict.values(): # see NetworkML_reader.py for projectionDict format
# is 'PG' part of the source population name and 'mitral' part of target:
if 'PG' in proj[0] and 'mitrals' in proj[1]:
for conn in proj[2]: # loop through the connections that are part of this projection
if mitstr in conn[2]: # if mitral_<mitralidx> is in the post_segment_path
### select the first PG that connects to this mitral mitralidx
### and connect a current clamp to it. also set up tables for the PG dend and mitral tuft.
if not found_PGmitsyn:
PG_path = conn[1]
# take the cellname part [-2] of PG_path, then take the last [-1] id part of cellname
PGidx = string.split( string.split(PG_path,'/')[-2], '_' )[-1]
PG = network.populationDict['PGs'][1][int(PGidx)]
PG.soma = moose.Compartment(get_matching_children(PG, ['Soma','soma'])[0]) # assumes at least one soma and takes the first!
self.PGTable = setupTable('PGTable',PG.soma,'Vm')
self.PGDendTable = setupTable('PGDendTable',moose.Compartment(conn[1]),'Vm') # pre_segment
PG_inject = 0.25e-9 # Amperes
ipulse_duration = 5e-3 # seconds
iPG = setup_iclamp(PG.soma, '_PG', SETTLETIME+RUNTIME/2.0, ipulse_duration, PG_inject)
self.tuftsegpath = conn[2]
post_seg = moose.Compartment(self.tuftsegpath)
### measure the Vm in the post_segment of the mitral by wrapping post_segment_path conn[2]
self.mittuftTable = setupTable('mittuftTable',post_seg,'Vm')
found_PGmitsyn = True
numsyns_thisPG_to_thismitral = 1
mitSegsList.append(self.tuftsegpath)
### find out how many times this selected PG connects to this mitral mitralidx
else:
comparedPG_path = conn[1]
# take the cellname part [-2] of PG_path, then take the last [-1] id part of cellname
comparedPGidx = string.split( string.split(comparedPG_path,'/')[-2], '_' )[-1]
if PGidx == comparedPGidx:
numsyns_thisPG_to_thismitral += 1
mitSegsList.append(conn[2])
if found_PGmitsyn: break
### I correct ALL the PG-|mitral Gbar for multiple PG-|mit synapses of selected PG to desired mitral
### I only activate the synapses I am interested in so it doesn't matter what I do to others!
### make a set (keep unique elements only) of the post-segments, so as not to correct any segment twice.
for segpath in set(mitSegsList):
post_seg = moose.Compartment(segpath)
PGmitsyn = moose.SynChan(get_matching_children(post_seg, ['PG_mitral'])[0])
PGmitsyn.Gbar = PGmitsyn.Gbar/numsyns_thisPG_to_thismitral
print "Corrected PG Gbar for selected PG",PGidx,"making",\
numsyns_thisPG_to_thismitral,"synapses to mitral",mitralidx
print "Also corrected granule Gbar for",GRANS_CLUB_SINGLES,\
"single grans clubbed and",PG_CLUB,"PGs clubbed."
print "Finally PG-|mit and gran-|mit synapses are each PG_CLUB =",\
PG_CLUB,"times the single synapse."
print 'Injecting granule_single',granidx,'with',gran_inject,\
'at',SETTLETIME,'s and PG',PGidx,'with',PG_inject,'at',SETTLETIME+RUNTIME/2.0,'s.'
def run_inhibition(self,network,args):
resetSim(network.context, SIMDT, PLOTDT) # from moose_utils.py sets clocks and resets
network.context.step(RUNTIME)
timevec = arange(0.0,RUNTIME+1e-10,SIMDT)
figure(facecolor='w')
plot(timevec,network.mitralTable[mitralidx]._vmTableSoma,'r-,',label='mitral soma Vm')
plot(timevec,self.mitdendTable,',-g',label=self.dendsegpath+' Vm')
plot(timevec,self.mittuftTable,',-b',label=self.tuftsegpath+' Vm')
legend(loc='lower right')
ylabel('SecDend is at %0.2f microns'%(self.dist*1e6,),fontsize='large')
xlabel('time (s)', fontsize='large')
figure()
plot(timevec,self.granTable,',-g',label='granule soma Vm')
plot(timevec,self.granDendTable,',-y',label='granule dend Vm')
plot(timevec,self.PGTable,',-b',label='PG soma Vm')
plot(timevec,self.PGDendTable,',-c',label='PG dend Vm')
legend(loc='upper right')
if args[1] == 'IPSC':
figure(facecolor='w')
#plot(timevec,self.mitITable,',-r',label='mitral soma Im')
plot(timevec,self.PIDITable,',-g',label='PID I to mitral')
legend(loc='upper right')
ylabel('I (A); SecDend is at %0.2f microns'%(self.dist*1e6,),fontsize='large')
xlabel('time (s)', fontsize='large')
#----------------------------------------------------
if __name__ == "__main__":
err_string = "You must tell me the type of simulation\
to run as a command line parameter:\n\
'lateral_granule' or 'PGvsGranule' or 'PGvsGranuleIPSC'"
if len(sys.argv) < 2:
print err_string
sys.exit(1)
sim_option = sys.argv[1]
if sim_option == 'lateral_granule':
sim = lateral_granule_inhibition()
includeProjections = ['granule_baseline']
args = []
elif sim_option == 'PGvsGranule':
sim = PGvsGranule()
includeProjections = []
# the post_segment on the mitral must be ~ this distance from the soma
args = [100e-6,'IPSP'] # meters
elif sim_option == 'PGvsGranuleIPSC':
sim = PGvsGranule()
includeProjections = []
# the post_segment on the mitral must be ~ this distance from the soma
args = [100e-6,'IPSC'] # meters
else:
print "Sorry wrong option.", err_string
sys.exit(1)
tweaks = build_tweaks( CLUB_MITRALS, NO_SPINE_INH, NO_SINGLES, NO_JOINTS,\
NO_MULTIS, NO_PGS, ONLY_TWO_MITS, includeProjections, (mitralidx,mitralsidekickidx) )
network = OBNetwork(OBNet_file, synchan_activation_correction,\
tweaks, mpirank, granfilebase, spiketable=False)
#printNetTree() # from moose_utils.py
sim.setup_stim(network, args)
spikes = True
tables = setupTables(network, NO_PGS, NO_SINGLES, NO_JOINTS, spikes=spikes)
sim.run_inhibition(network, args) # tests simset_inhibition i.e. inhibition between two mitrals
if spikes:
bins = 20
timevec = arange(0.0,REALRUNTIME,REALRUNTIME/float(bins))
plot_extras_spikes(timevec, tables, NO_PGS, NO_SINGLES, NO_JOINTS, bins, RUNTIME, SETTLETIME)
else:
timevec = arange(0.0,RUNTIME+1e-12,PLOTDT)
plot_extras(timevec, tables, NO_PGS, NO_SINGLES, NO_JOINTS, '')
show()
